A
Senior AI Engineer (Investment Management)
Apollo Solutions
4 hours ago
Full-time
On-site
Boston, Massachusetts, United States
Boston | Hybrid – 3 days per week onsite
I’m working with a highly sophisticated, data-driven investment organisation that is building out its AI engineering capability within the Investment function.
This is an opportunity for a senior AI Engineer to work directly alongside
quantitative researchers and portfolio managers , turning real investment workflows into production-grade AI systems.
This is
not a research-only AI role
and it isn't simply about experimenting with the latest LLMs. The focus is on building technology that is genuinely useful to investment professionals: agentic workflows, reusable AI skills and automation that can safely accelerate research and portfolio processes.
The opportunity You will sit close to the Investment teams, working with domain experts to identify opportunities where AI can meaningfully improve productivity and decision support.
You'll be responsible for taking often ambiguous investment requirements and turning them into well-defined, production-ready software.
This includes:
Designing, building and operating
LLM-powered and agentic workflows
for investment use cases
Developing reusable AI skills that encode investment workflows and institutional knowledge
Working directly with quantitative researchers and portfolio managers to prototype and productionise solutions
Building robust
Python and AWS
services and integrating them into existing production environments
Establishing appropriate human-in-the-loop review, testing and controlled execution
Designing guardrails around data access, agent scope, cost and reliability
Translating investment intent into clear technical specifications and well-scoped engineering work
Measuring the real-world impact of AI workflows through adoption, quality and time-to-value
Establishing sensible review, auditability and accountability standards around AI-generated changes
Helping shape best practices around agentic and instruction-driven development as the technology evolves
What we're looking for We're particularly interested in engineers who combine
strong software engineering fundamentals with genuine interest or experience in investment environments .
You should have:
Significant experience delivering
production-grade software or AI systems
Hands-on experience building and operating
LLM, GenAI or agentic systems
Strong
Python and AWS
experience
Strong engineering practices across testing, Git/version control and CI/CD
Experience taking complex or ambiguous business/domain requirements and turning them into reliable software
Experience working closely with sophisticated technical or domain experts
An understanding of systematic, quantitative or institutional investment processes
Good judgement around the trade-offs between
quality, speed, cost and risk
A pragmatic mindset: you care about whether an AI system actually works and creates value, not simply whether the technology is impressive
A background in
quantitative finance, systematic investing, hedge funds, asset management or financial technology
would be particularly valuable.
The type of engineer we're looking for The strongest candidates are likely to be people who can comfortably sit between
AI engineering and investment .
You might currently be a:
Senior / Staff Software Engineer working heavily with GenAI
Quant Developer with substantial recent AI/LLM experience
Engineer embedded within a quantitative research or investment team
The common denominator is
hands-on production engineering
combined with the ability to understand a complex domain and build technology around it.
This would suit someone who wants to move beyond generic enterprise AI and work on
AI that directly interacts with the investment decision-making process .
If you're an AI Engineer who wants to work at the intersection of
agentic AI, software engineering and quantitative investing , I'd be very interested in speaking with you.
#J-18808-Ljbffr
This is an opportunity for a senior AI Engineer to work directly alongside
quantitative researchers and portfolio managers , turning real investment workflows into production-grade AI systems.
This is
not a research-only AI role
and it isn't simply about experimenting with the latest LLMs. The focus is on building technology that is genuinely useful to investment professionals: agentic workflows, reusable AI skills and automation that can safely accelerate research and portfolio processes.
The opportunity You will sit close to the Investment teams, working with domain experts to identify opportunities where AI can meaningfully improve productivity and decision support.
You'll be responsible for taking often ambiguous investment requirements and turning them into well-defined, production-ready software.
This includes:
Designing, building and operating
LLM-powered and agentic workflows
for investment use cases
Developing reusable AI skills that encode investment workflows and institutional knowledge
Working directly with quantitative researchers and portfolio managers to prototype and productionise solutions
Building robust
Python and AWS
services and integrating them into existing production environments
Establishing appropriate human-in-the-loop review, testing and controlled execution
Designing guardrails around data access, agent scope, cost and reliability
Translating investment intent into clear technical specifications and well-scoped engineering work
Measuring the real-world impact of AI workflows through adoption, quality and time-to-value
Establishing sensible review, auditability and accountability standards around AI-generated changes
Helping shape best practices around agentic and instruction-driven development as the technology evolves
What we're looking for We're particularly interested in engineers who combine
strong software engineering fundamentals with genuine interest or experience in investment environments .
You should have:
Significant experience delivering
production-grade software or AI systems
Hands-on experience building and operating
LLM, GenAI or agentic systems
Strong
Python and AWS
experience
Strong engineering practices across testing, Git/version control and CI/CD
Experience taking complex or ambiguous business/domain requirements and turning them into reliable software
Experience working closely with sophisticated technical or domain experts
An understanding of systematic, quantitative or institutional investment processes
Good judgement around the trade-offs between
quality, speed, cost and risk
A pragmatic mindset: you care about whether an AI system actually works and creates value, not simply whether the technology is impressive
A background in
quantitative finance, systematic investing, hedge funds, asset management or financial technology
would be particularly valuable.
The type of engineer we're looking for The strongest candidates are likely to be people who can comfortably sit between
AI engineering and investment .
You might currently be a:
Senior / Staff Software Engineer working heavily with GenAI
Quant Developer with substantial recent AI/LLM experience
Engineer embedded within a quantitative research or investment team
The common denominator is
hands-on production engineering
combined with the ability to understand a complex domain and build technology around it.
This would suit someone who wants to move beyond generic enterprise AI and work on
AI that directly interacts with the investment decision-making process .
If you're an AI Engineer who wants to work at the intersection of
agentic AI, software engineering and quantitative investing , I'd be very interested in speaking with you.
#J-18808-Ljbffr